A hybrid named entity recognizer for Turkish with applications to different text genres

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this study, we present a hybrid named entity recognizer for Turkish, which is based on a previously proposed rule based recognizer. Since rule based systems for specic domains require their knowledge sources to be manually revised when ported to other domains, we turn the rule based recognizer into a hybrid one so that it learns from annotated data and improves its knowledge sources accordingly. Both the hybrid recognizer and its predecessor are evaluated on the same corpora and the hybrid recognizer achieves comparably better results. The current study is significant since it presents the first hybrid -manually engineered and learning-named entity recognizer for Turkish texts.

Original languageEnglish
Title of host publicationComputer and Information Sciences - Proceedings of the 25th International Symposium on Computer and Information Sciences
Pages113-116
Number of pages4
DOIs
Publication statusPublished - 2010
Event25th International Symposium on Computer and Information Sciences, ISCIS 2010 - London, United Kingdom
Duration: Sept 22 2010Sept 24 2010

Publication series

NameLecture Notes in Electrical Engineering
Volume62 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference25th International Symposium on Computer and Information Sciences, ISCIS 2010
Country/TerritoryUnited Kingdom
CityLondon
Period9/22/109/24/10

Keywords

  • information extraction
  • named entity recognition
  • Turkish

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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